Two major policy approaches are used currently to motivate hospitals to prevent hospital-acquired complications (HACs): 1) public reporting of hospital performance regarding patient safety (e.g., the website Hospital Compare), and 2) value-based purchasing, which ties hospital payment with better patient outcomes, such as the Hospital-Acquired Conditions Initiative implemented by the Centers for Medicare & Medicaid Services (CMS) to stop hospitals from receiving extra payment for specific reasonably preventable complications. This CMS initiative also enables public reporting of HACs by requiring hospitals to identify discharge diagnoses as present-on-admission or not (i.e., hospital-acquired), changing a routinely-generated administrative dataset into a new data source to generate rates of HACs to compare hospitals. Though intended to improve patient safety (and save money), these changes regarding data collection, payment, and public reporting of HACs have occurred without preliminary evaluations concerning: 1) the validity of these new data regarding HAC rates, and 2) what clinical impacts these changes may have on patients. These two knowledge gaps are significant, as public reporting of other patient outcomes (e.g., hospital mortality) has demonstrated that evaluating and reporting outcome data is complicated, and can have both intended and unintended consequences for patients - particularly for complex patients (i.e., with multiple chronic conditions) with higher baseline risks for poor outcomes including HACs. The candidate Dr. Jennifer Meddings, who will focus her research on the growing population of complex patients, will pursue a mentored research plan designed to enhance her skills concerning methods needed to evaluate the clinical impact of quality improvement initiatives for complex patients, with two specific aims: Aim 1. To validate measures of hospital-acquired complications derived from administrative data as indicators of hospital quality, by triangulation with measures from different data sources. Aim 2. To evaluate unintended outcomes (i.e., collateral benefits and damages) for patients as downstream or spillover effects of non-payment and public reporting for specific hospital-acquired complications, with a focus on impacts for complex patients. Using multiple years of patient-level administrative data, Aim 2's analyses will focus on three outcomes that could improve (as collateral benefit) or worsen (as collateral damage) as hospitals respond to non-payment or public reporting for specific HACs: 1) early readmission, 2) level of care after discharge (such skilled nursing facility), and 3) secondary complications, related to developing or treating the initial HAC. This research and advanced coursework will facilitate Dr. Meddings's development into a leading independent investigator in performance measurement and improvement, whose research will inform policy decisions to improve care for complex patients.